Ultra Light OCR Competition Technical Report
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Abstract (arXiv)
Ultra Light OCR Competition is a Chinese scene text recognition competition jointly organized by CSIG (China Society of Image and Graphics) and Baidu, Inc. In addition to focusing on common problems in Chinese scene text recognition, such as long text length and massive characters, we need to balance the trade-off of model scale and accuracy since the model size limitation in the competition is 10M. From experiments in aspects of data, model, training, etc, we proposed a general and effective method for Chinese scene text recognition, which got us second place among over 100 teams with accuracy 0.817 in TestB dataset. The code is available at https://aistudio.baidu.com/aistudio/projectdetail/2159102.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 7 of its 8 references that are in the map. First posted on arXiv 25 Oct 2021.
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References · 7
- 2019Searching for MobileNetV3cited by 1,984
- 2019Deep Double Descent: Where Bigger Models and More Data Hurtcited by 667
- 2018Albumentations: fast and flexible image augmentationscited by 558
- 2015An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognitioncited by 519
- 2014Efficient Object Localization Using Convolutional Networkscited by 226
- 2020Learn to Augment: Joint Data Augmentation and Network Optimization for Text Recognitioncited by 36
- 2020Text Recognition in the Wild: A Surveycited by 29
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